Loneliness and social isolation are known to be associated with depression, general anxiety, and social anxiety. However, knowledge on the overlapping and unique features of these relationships, while differentiating between social loneliness (perceived absence of an acceptable social network) and emotional loneliness (perceived absence of close connections), is lacking. We constructed a network analysis to examine the relationships between self-reported social loneliness, emotional loneliness, social isolation, depression, general anxiety and social anxiety in a large sample of university students (N = 7314, 67.4 % female, range 16.3-75.8 years, M_age = 23.9, SD_age = 5.7). Hierarchical regression analyses were used to examine whether depression, general anxiety and social anxiety moderated the relationship between social isolation and loneliness types. As comorbidity between anxiety and depression is high, the role of anxiety as a moderator in the relationship between depression and loneliness types was also examined. The network analysis showed that social loneliness was most strongly explained by social isolation, whereas emotional loneliness was most strongly explained by social anxiety and depression. General anxiety was solely related to loneliness through depression. The regression analyses showed that general and social anxiety and depression did not moderate the relationship between social isolation and loneliness types. Differences found between loneliness types may be influenced by a methodological artifact of the DJGLS. These findings highlight the importance of social anxiety over general anxiety in relation to loneliness. Also, it showed unique relationships for social- and emotional loneliness with psycho-social variables, which has important implications for research- and clinical settings.

Common mental disorders, such as depression and anxiety, often emerge in college students during the transition into early adulthood. Mental health problems can seriously impact students' functioning, interpersonal relationships, and academic achievement. Actively reaching out to college students with mental health problems and offering them internet-based interventions may be a promising way of providing low-threshold access to evidence-based treatment in colleges. This randomized controlled trial aimed to assess the effectiveness of a guided web-based transdiagnostic individually tailored Cognitive Behavioral Therapy (iCBT) in treating college students with depression and/or anxiety symptoms. Through an online survey that screened college students' mental health, we recruited 100 college students aged ≥18 years who reported mild to moderate depression and/or anxiety symptoms and were attending colleges in the Netherlands. Participants were randomly allocated to guided iCBT (n = 48) or treatment as usual (TAU) control (n = 52). Primary outcomes were symptoms of depression and anxiety measured at post-treatment (7 weeks post-randomization). We also measured all outcomes at 6- and 12-months post-randomization. All analyses were based on the intention-to-treat principle and were repeated using the complete-case sample. We found no evidence of a difference between the effects of guided iCBT and TAU in any of the examined outcomes (i.e., symptoms of depression and anxiety, quality of life, educational achievement, and college dropout) across all time points (p > .05). There was no evidence that effects of iCBT were associated with treatment satisfaction and adherence. More research into transdiagnostic individually tailored iCBT is necessary. Further, future studies should recruit larger samples to investigate possible smaller but clinically relevant effects of internet-based interventions for college students with depression and/or anxiety.